The subject herein generally relates to a system and method to manage progression of a patient through a workflow, and in particular, the workflow is a healthcare procedure.
Hospitals and other medical facilities (e.g., imaging centers, cardiology treatment centers, emergency rooms, surgical suites, etc.) include various workflows to deliver diagnosis or treatment to admitted patients. These workflows are comprised of events that employ various resources, such as imaging rooms, physicians, nurses, radiologists, cardiologists, clinicians, technicians, or transcriptionists. These workflows are often unstructured and non-linear in nature due to complex conditions that dynamically evolve at any point in time of the workflow.
Known systems and methods to manage patients through these workflows delivered at healthcare facilities are generally static and non-adaptive. These known systems generally rely on past data and linear design assumptions to manage workflows (e.g., diagnostic imaging, cardiac treatment, etc.). As a result, these known systems and methods are generally inflexible or unresponsive to non-linear changes or events that increase the likelihood of chaos due to complex conditions that evolve in real time beyond the original linear design. Examples of parameters to measure a quality of service or efficiency of workflows include, but are not limited to, patient wait times, procedure turn-around times, resource utilization, etc. For example, increasing procedure turn-around times can increase underutilization of resources (e.g., an imaging room sitting idle).